Evaluating Injury Severity in Neonatal Encephalopathy Using Automated Quantitative Electroencephalography Analysis: A Pilot Study.

Quantitative analysis of electroencephalography (qEEG) is a potential source of biomarkers for neonatal encephalopathy (NE). However, prior studies using qEEG in NE were limited in their generalizability due to individualized techniques for calculating qEEG features or labor-intensive pre-selection of EEG data. We piloted a fully automated method using commercially available software to calculate the suppression ratio (SR), absolute delta power, and relative delta, theta, alpha, and beta power from EEG of neonates undergoing 72 h of therapeutic hypothermia (TH) for NE between April 20, 2018, and November 4, 2019. We investigated the association of qEEG with degree of encephalopathy (modified Sarnat score), severity of neuroimaging abnormalities following TH (National Institutes of Child Health and Development Neonatal Research Network [NICHD-NRN] score), and presence of seizures. Thirty out of 38 patients met inclusion criteria. A more severe modified Sarnat score was associated with higher SR during all phases of TH, lower absolute delta power during all phases except rewarming, and lower relative delta power during the last 24 h of TH. In 21 patients with neuroimaging data, a worse NICHD-NRN score was associated with higher SR, lower absolute delta power, and higher relative beta power during all phases. QEEG features were not significantly associated with the presence of seizures after correction for multiple comparisons. Our results are consistent with those of prior studies using qEEG in NE and support automated qEEG analysis as an accessible, generalizable method for generating biomarkers of NE and response to TH. Additionally, we found evidence of an immature relative frequency composition in neonates with more severe brain injury, suggesting that automated qEEG analysis may have a use in the assessment of brain maturity.

The stability of slow-wave sleep and EEG oscillations across two consecutive nights of laboratory polysomnography in cognitively normal older adults.

Laboratory polysomnography provides gold-standard measures of sleep physiology, but multi-night investigations are resource intensive. We assessed the night-to-night stability via reproducibility metrics for sleep macrostructure and electroencephalography oscillations in a group of cognitively normal adults attending two consecutive polysomnographies. Electroencephalographies were analysed using an automatic algorithm for detection of slow-wave activity, spindle and K-complex densities. Average differences between nights for sleep macrostructure, electroencephalography oscillations and sleep apnea severity were assessed, and test-retest reliability was determined using two-way intraclass correlations. Agreement was calculated using the smallest real differences between nights for all measures. Night 2 polysomnographies showed significantly greater time in bed, total sleep time (6.3 hr versus 6.8 hr, p < 0.001) and percentage of rapid eye movement sleep (17.5 versus 19.7, p < 0.001). Intraclass correlations were low for total sleep time, percentage of rapid eye movement sleep and sleep efficiency, moderate for percentage of slow-wave sleep and percentage of non-rapid eye movement 2 sleep, good for slow-wave activity and K-complex densities, and excellent for spindles and apnea-hypopnea index with hypopneas defined according to 4% oxygen desaturation criteria only. The smallest real difference values were proportionally high for most sleep macrostructure measures, indicating moderate agreement, and proportionally lower for most electroencephalography microstructure variables. Slow waves, K-complexes, spindles and apnea severity indices are highly reproducible across two consecutive nights of polysomnography. In contrast, sleep macrostructure measures all demonstrated poor reproducibility as indicated by low intraclass correlation values and moderate agreement. Although there were average differences in percentage of rapid eye movement sleep and total sleep time, these were numerically small and perhaps functionally or clinically less significant. One night of in-laboratory polysomnography is enough to provide stable, reproducible estimates of an individual's sleep concerning measures of slow-wave activity, spindles, K-complex densities and apnea severity.

Quantitative EEG in the Differential Diagnosis of Dementia Subtypes.

OBJECTIVE: Most neurodegenerative dementias present with substantial overlap in clinical features. Therefore, differential diagnosis is often a challenging task necessitating costly and sometimes invasive diagnostic procedures. A promising, non-invasive and cost-effective method is the widely available electroencephalography (EEG). METHODS: Twenty-three subjects with Alzheimer's disease (AD), 28 subjects with dementia with Lewy bodies (DLB), 15 subjects with frontotemporal dementias (FTDs), and 22 healthy controls (HC) were enrolled. Nineteen channel computerized EEG recordings were acquired. Mean relative powers were calculated using the standard frequency bands. Theta/alpha ratio (TAR), theta/beta ratio (TBR), a spectral index of (alpha + beta)/(theta + delta) and an alpha reactivity index (alpha in eyes-open condition/alpha in eyes-closed condition) were also calculated. Receiver operating characteristic (ROC) analyses were performed to assess diagnostic accuracy. RESULTS: For the comparison of EEG measures across groups, we performed a multivariate ANOVA followed by univariate ANOVAs controlling for the effects of age, with post hoc tests. Theta power and TBR were increased in DLB compared to other groups. Alpha power was decreased in DLB compared to HC and FTD; and in AD compared to FTD. Beta power was decreased in DLB compared to AD and HC. Furthermore, regional analyses demonstrated a unique pattern of theta power increase in DLB; affecting frontal, central, parietal, occipital, and temporal regions. In AD, theta power increased compared to HC in parietal, occipital, and right temporal regions. TAR was increased in DLB compared to other groups; and in AD compared to HC. Finally, alpha reactivity index was higher in DLB compared to HC and FTD. In AD, EEG slowing was associated with cognitive impairment, while in DLB, this was associated with higher DLB characteristics. In the ROC analyses to distinguish DLB from FTD and AD, measures of EEG slowing yielded high area under curve values, with good specificities. Also, decreased alpha reactivity could distinguish DLB from FTD with good specificity. EEG slowing in DLB showed a diffuse pattern compared to AD, where a posterior and temporal slowing predominated. CONCLUSION: We showed that EEG slowing was satisfactory in distinguishing DLB patients from AD and FTD patients. Notably, this slowing was a characteristic finding in DLB patients, even at early stages, while it paralleled disease progression in AD. Furthermore, EEG slowing in DLB showed a diffuse pattern compared to AD, where a posterior and temporal slowing predominated. These findings align with the previous evidence of the diencephalic dysfunction in DLB.

Quantitative electroencephalography (qEEG), apolipoprotein A-I (APOA-I), and apolipoprotein epsilon 4 (APOE ɛ4) alleles for the diagnosis of mild cognitive impairment and Alzheimer's disease.

INTRODUCTION: Alzheimer's disease (AD) is the most common type of dementia. Amnestic mild cognitive impairment (aMCI), a pre-dementia stage is an important stage for early diagnosis and intervention. This study aimed to investigate the diagnostic value of qEEG, APOA-I, and APOE ɛ4 allele in aMCI and AD patients and found the correlation between qEEG (Delta + Theta)/(Alpha + Beta) ratio (DTABR) and different cognitive domains. METHODS: All participants were divided into three groups: normal controls (NCs), aMCI, and AD, and all received quantitative electroencephalography (qEEG), neuropsychological scale assessment, apolipoprotein epsilon 4 (APOE ɛ4) alleles, and various blood lipid indicators. Different statistical methods were used for different data. RESULTS: The cognitive domains except executive ability were all negatively correlated with DTABR in different brain regions while executive ability was positively correlated with DTABR in several brain regions, although without statistical significance. The consequences confirmed that the DTABR of each brain area were related to MMSE, MoCA, instantaneous memory, and the language ability (p < 0.05), and the DTABR in the occipital area was relevant to all cognitive domains (p < 0.01) except executive function (p = 0.272). Also, occipital DTABR was most correlated with language domain when tested by VFT with a moderate level (r = 0.596, p < 0.001). There were significant differences in T3, T5, and P3 DTABR between both AD and NC and aMCI and NCs. As for aMCI diagnosis, the maximum AUC was achieved when using T3 combined with APOA-I and APOE ε4 (0.855) and the maximum AUC was achieved when using T5 combined with APOA-I and APOE ε4 (0.889) for AD diagnosis. CONCLUSION: These findings highlight that APOA-I, APOE ɛ4, and qEEG play an important role in aMCI and AD diagnosis. During AD continuum, qEEG DTABR should be taken into consideration for the early detection of AD risk.

Sleep electroencephalography biomarkers of cognition in obstructive sleep apnea.

Obstructive sleep apnea has been associated with cognitive impairment and may be linked to disorders of cognitive function. These associations may be a result of intermittent hypoxaemia, sleep fragmentation and changes in sleep microstructure in obstructive sleep apnea. Current clinical metrics of obstructive sleep apnea, such as the apnea-hypopnea index, are poor predictors of cognitive outcomes in obstructive sleep apnea. Sleep microstructure features, which can be identified on sleep electroencephalography of traditional overnight polysomnography, are increasingly being characterized in obstructive sleep apnea and may better predict cognitive outcomes. Here, we summarize the literature on several major sleep electroencephalography features (slow-wave activity, sleep spindles, K-complexes, cyclic alternating patterns, rapid eye movement sleep quantitative electroencephalography, odds ratio product) identified in obstructive sleep apnea. We will review the associations between these sleep electroencephalography features and cognition in obstructive sleep apnea, and examine how treatment of obstructive sleep apnea affects these associations. Lastly, evolving technologies in sleep electroencephalography analyses will also be discussed (e.g. high-density electroencephalography, machine learning) as potential predictors of cognitive function in obstructive sleep apnea.

Review of Noninvasive Neuromonitoring Modalities in Children II: EEG, qEEG.

Critically ill children with acute neurologic dysfunction are at risk for a variety of complications that can be detected by noninvasive bedside neuromonitoring. Continuous electroencephalography (cEEG) is the most widely available and utilized form of neuromonitoring in the pediatric intensive care unit. In this article, we review the role of cEEG and the emerging role of quantitative EEG (qEEG) in this patient population. cEEG has long been established as the gold standard for detecting seizures in critically ill children and assessing treatment response, and its role in background assessment and neuroprognostication after brain injury is also discussed. We explore the emerging utility of both cEEG and qEEG as biomarkers of degree of cerebral dysfunction after specific injuries and their ability to detect both neurologic deterioration and improvement.

Neuromonitoring in Children with Cerebrovascular Disorders.

BACKGROUND: Cerebrovascular disorders are an important cause of morbidity and mortality in children. The acute care of a child with an ischemic or hemorrhagic stroke or cerebral sinus venous thrombosis focuses on stabilizing the patient, determining the cause of the insult, and preventing secondary injury. Here, we review the use of both invasive and noninvasive neuromonitoring modalities in the care of pediatric patients with arterial ischemic stroke, nontraumatic intracranial hemorrhage, and cerebral sinus venous thrombosis. METHODS: Narrative review of the literature on neuromonitoring in children with cerebrovascular disorders. RESULTS: Neuroimaging, near-infrared spectroscopy, transcranial Doppler ultrasonography, continuous and quantitative electroencephalography, invasive intracranial pressure monitoring, and multimodal neuromonitoring may augment the acute care of children with cerebrovascular disorders. Neuromonitoring can play an essential role in the early identification of evolving injury in the aftermath of arterial ischemic stroke, intracranial hemorrhage, or sinus venous thrombosis, including recurrent infarction or infarct expansion, new or recurrent hemorrhage, vasospasm and delayed cerebral ischemia, status epilepticus, and intracranial hypertension, among others, and this, is turn, can facilitate real-time adjustments to treatment plans. CONCLUSIONS: Our understanding of pediatric cerebrovascular disorders has increased dramatically over the past several years, in part due to advances in the neuromonitoring modalities that allow us to better understand these conditions. We are now poised, as a field, to take advantage of advances in neuromonitoring capabilities to determine how best to manage and treat acute cerebrovascular disorders in children.

Comparative analysis of background EEG activity based on MRI findings in neonatal hypoxic-ischemic encephalopathy: a standardized, low-resolution, brain electromagnetic tomography (sLORETA) study.

BACKGROUND: It is important to assess the degree of brain injury and predict long-term outcomes in neonates diagnosed with hypoxic-ischemic encephalopathy (HIE). However, routine studies, including magnetic resonance imaging (MRI) and conventional encephalography (EEG) or amplitude-integrated EEG (aEEG), have their own limitations in terms of availability and accuracy of evaluation. Recently, quantitative EEG (qEEG) has been shown to improve the predictive reliability of neonatal HIE and has been further refined with brain mapping techniques. METHODS: We investigated background EEG activities in 29 neonates with HIE who experienced therapeutic hypothermia, via qEEG using a distributed source model. MRI images were evaluated and classified into two groups (normal-to-mild injury vs moderate-to-severe injury), based on a scoring system. Non-parametric statistical analysis using standardized low-resolution brain electromagnetic tomography was performed to compare the current density distribution of four frequency bands (delta, theta, alpha, and beta) between the two groups. RESULTS: Electrical neuronal activities were significantly lower in the moderate-to-severe injury group compared with the normal-to-mild injury group. Background EEG activities in moderate-to-severe HIE were most significantly reduced in the temporal and parietal lobes. Quantitative EEG also revealed a decrease in background activity at all frequency bands, with a maximum in decrease in the delta component. The maximum difference in current density was found in the inferior parietal lobule of the right parietal lobe for the delta frequency band. CONCLUSIONS: Our study demonstrated quantitative and topographical changes in EEG in moderate-to-severe neonatal HIE. They also suggest possible implementation and evaluation of conventional EEG and aEEG in neonatal HIE. The findings have implications as biomarkers in the assessment of neonatal HIE.

Comparative analysis of background EEG activity in juvenile myoclonic epilepsy during valproic acid treatment: a standardized, low-resolution, brain electromagnetic tomography (sLORETA) study.

BACKGROUND: By definition, the background EEG is normal in juvenile myoclonic epilepsy (JME) patients and not accompanied by other developmental and cognitive problems. However, some recent studies using quantitative EEG (qEEG) reported abnormal changes in the background activity. QEEG investigation in patients undergoing anticonvulsant treatment might be a useful approach to explore the electrophysiology and anticonvulsant effects in JME. METHODS: We investigated background EEG activity changes in patients undergoing valproic acid (VPA) treatment using qEEG analysis in a distributed source model. In 17 children with JME, non-parametric statistical analysis using standardized low-resolution brain electromagnetic tomography was performed to compare the current density distribution of four frequency bands (delta, theta, alpha, and beta) between untreated and treated conditions. RESULTS: VPA reduced background EEG activity in the low-frequency (delta-theta) bands across the frontal, parieto-occipital, and limbic lobes (threshold log-F-ratio = ±1.414, p < 0.05; threshold log-F-ratio= ±1.465, p < 0.01). In the delta band, comparative analysis revealed significant current density differences in the occipital, parietal, and limbic lobes. In the theta band, the analysis revealed significant differences in the frontal, occipital, and limbic lobes. The maximal difference was found in the delta band in the cuneus of the left occipital lobe (log-F-ratio = -1.840) and the theta band in the medial frontal gyrus of the left frontal lobe (log-F-ratio = -1.610). CONCLUSIONS: This study demonstrated the anticonvulsant effects on the neural networks involved in JME. In addition, these findings suggested the focal features and the possibility of functional deficits in patients with JME.

Quantitative EEG-Based Seizure Estimation in Super-Refractory Status Epilepticus.

BACKGROUND: The objective of this study was to evaluate the accuracy of seizure burden in patients with super-refractory status epilepticus (SRSE) by using quantitative electroencephalography (qEEG). METHODS: EEG recordings from 69 patients with SRSE (2009-2019) were reviewed and annotated for seizures by three groups of reviewers: two board-certified neurophysiologists using only raw EEG (gold standard), two neurocritical care providers with substantial experience in qEEG analysis (qEEG experts), and two inexperienced qEEG readers (qEEG novices) using only a qEEG trend panel. RESULTS: Raw EEG experts identified 35 (51%) patients with seizures, accounting for 2950 seizures (3,126 min). qEEG experts had a sensitivity of 93%, a specificity of 61%, a false positive rate of 6.5 per day, and good agreement (κ = 0.64) between both qEEG experts. qEEG novices had a sensitivity of 98.5%, a specificity of 13%, a false positive rate of 15 per day, and fair agreement (κ = 0.4) between both qEEG novices. Seizure burden was not different between the qEEG experts and the gold standard (3,257 vs. 3,126 min), whereas qEEG novices reported higher burden (6066 vs. 3126 min). CONCLUSIONS: Both qEEG experts and novices had a high sensitivity but a low specificity for seizure detection in patients with SRSE. qEEG could be a useful tool for qEEG experts to estimate seizure burden in patients with SRSE.

Comparison of QEEG Findings before and after Onset of Post-COVID-19 Brain Fog Symptoms.

Previous research and clinical reports have shown that some individuals after COVID-19 infection may demonstrate symptoms of so-called brain fog, manifested by cognitive impairment and disorganization in behavior. Meanwhile, in several other conditions, related to intellectual function, a specific pattern of changes in electric brain activity, as recorded by quantitative electroencephalography (QEEG) has been documented. We hypothesized, that in post-COVID brain fog, the subjective complaints may be accompanied by objective changes in the QEEG profile. In order to test this hypothesis, we have performed an exploratory study on the academic staff of our University with previous records of QEEG originating in the pre-COVID-19 era. Among them, 20 subjects who revealed neurological problems in the cognitive sphere (confirmed as covid fog/brain fog by a clinical specialist) after COVID-19 infection were identified. In those individuals, QEEG was performed. We observed, that opposite to baseline QEEG records, increased Theta and Alpha activity, as well as more intensive sensimotor rhythm (SMR) in C4 (right hemisphere) in relation to C3 (left hemisphere). Moreover, a visible increase in Beta 2 in relation to SMR in both hemispheres could be documented. Summarizing, we could demonstrate a clear change in QEEG activity patterns in individuals previously not affected by COVID-19 and now suffering from post-COVID-19 brain fog. These preliminary results warrant further interest in delineating their background. Here, both neuroinflammation and psychological stress, related to Sars-CoV2-infection may be considered. Based on our observation, the relevance of QEEG examination as a supportive tool for post-COVID clinical workup and for monitoring the treatment effects is also to be explored.

IMPLEMENTATION OF QUANTITATIVE ELECTROENCEPHALOGRAPHY TO IMPROVE EFFICACY OF DIAGNOSIS AND TREATMENT MANAGEMENT OF CHRONIC CEREBRAL ISCHEMIA.

OBJECTIVE: The aim: To improve the effectiveness of diagnosis and treatment of chronic cerebral ischemia through the use of quantitative electroencephalography in civil servants on the outpatient and hospital stage. PATIENTS AND METHODS: Materials and methods: A total of 150 patients (59 males and 91 females) aged from 40 to 69 years were examined. The patients were divided into three groups statistically correlated with the main disease - chronic cerebral ischemia (CCI), degree of severity - CCI level 2, age and statistical status. Registration of brain biopotentials was performed using a computerized electroencephalograph of «TredexExpert¼ series. The total spectral power capacity - ASP (µV/√Hz), relative power capacity - RSP (%) were studied in the investigated frequency ranges. RESULTS: Results: The study of three groups of patients with CCI of different genesis, an increase in ASP of all studied ranges, but of varying degrees of severity, was found: first, delta and theta ranges, then beta ranges, and finally, to a lesser extent, ASP of the alpha1 range and alphaS range. Therefore, the RSP of alpha1- and alphaS-bands significantly decreased in all studied groups. CONCLUSION: Conclusions: 1. In all studied groups, the relative spectral power of the alpha 1 and alphaS bands decreased significantly. An increase in the relative spectral power of the beta-frequency rhythm in all leads was established. 2. The identified neurophysiological differences in the formation and course of dyscirculatory encephalopathy of various genesis are used to monitor the effectiveness of treatment of chronic brain ischemia.

Does Quantitative Electroencephalography Refine Preoperative Cognitive Assessment in Parkinson's Disease Patients Treated with Deep Brain Stimulation? A Follow-Up Study.

OBJECTIVE: Deep brain stimulation (DBS) in Parkinson's disease (PD) is associated with an increased risk of post-operative cognitive deterioration. Preoperative neuropsychological testing can be affected and limited by the patient's collaboration in advanced disease. The purpose of this study was to determine whether preoperative quantitative electroencephalography (qEEG) may be a useful complementary examination technique during preoperative assessment to predict cognitive changes in PD patients treated with DBS. METHODS: We compared the cognitive performance of 16 PD patients who underwent bilateral subthalamic nucleus DBS to the performance of 15 PD controls (matched for age, sex, and education) at baseline and at 24 months. Cognitive scores were calculated for all patients across 5 domains. A preoperative 256-channel resting EEG was recorded from each patient. We computed the global relative power spectra. Correlation and linear regression models were used to assess associations of preoperative EEG measures with post-operative cognitive scores. RESULTS: Slow waves (relative delta and theta band power) were negatively correlated with post-operative cognitive performance, while faster waves (alpha 1) were strongly positively correlated with the same scores (the overall cognitive score, attention, and executive function). Linear models revealed an association of delta power with the overall cognitive score (p = 0.00409, adjusted R2 = 0.6341). Verbal fluency (VF) showed a significant decline after DBS surgery, which was correlated with qEEG measures. CONCLUSIONS: To analyse the side effects after DBS in PD patients, the most important parameter is verbal fluency capacity. In addition, correlation with EEG frequency bands might be useful to detect particularly vulnerable patients for cognitive impairment and be supportive in the selection process of patients considered for DBS.

Slowing on quantitative EEG is associated with transition to dementia in mild cognitive impairment.

Electroencephalographic (EEG) abnormalities are greater in mild cognitive impairment (MCI) with Lewy bodies (MCI-LB) than in MCI due to Alzheimer's disease (MCI-AD) and may anticipate the onset of dementia. We aimed to assess whether quantitative EEG (qEEG) slowing would predict a higher annual hazard of dementia in MCI across these etiologies. MCI patients (n = 92) and healthy comparators (n = 31) provided qEEG recording and underwent longitudinal clinical and cognitive follow-up. Associations between qEEG slowing, measured by increased theta/alpha ratio, and clinical progression from MCI to dementia were estimated with a multistate transition model to account for death as a competing risk, while controlling for age, cognitive function, and etiology classified by an expert consensus panel.Over a mean follow-up of 1.5 years (SD = 0.5), 14 cases of incident dementia and 5 deaths were observed. Increased theta/alpha ratio on qEEG was associated with increased annual hazard of dementia (hazard ratio = 1.84, 95% CI: 1.01-3.35). This extends previous findings that MCI-LB features early functional changes, showing that qEEG slowing may anticipate the onset of dementia in prospectively identified MCI.

Electroencephalography-based cortical sources of working memory in the subjects with opioid addiction: A pilot study.

Background & objectives: Working memory impairments in the subjects of opioid addiction may stem from an aberrant cortical activity in the executive areas, and may help in early identification of individuals with addictive tendencies and may also be used as a neurofeedback mechanism in adjunct to the existing therapeutics. Methods: Electrical neuroimaging via 128-channel electroencephalography (EEG) recording was done in 15 male subjects with opioid addiction (29.45±5.6 yr) during the performance of Sternberg Working Memory Task. EEG data were acquired and analyzed for cortical sources during task as compared to resting (baseline) condition. Results: Working memory deficits were manifested as decrease in accuracy percentage in the subjects with opioid addiction, while no significant difference was seen in reaction time, on comparison with laboratory-acquired matched controls. Standardized low-resolution brain electromagnetic tomography (sLORETA)-based EEG source analysis revealed higher cortical activity in the anterior cingulate cortex, inferior, middle and superior temporal gyri, inferior frontal gyrus, superior parietal lobule, inferior parietal lobule and precuneus, whereas significant lower activity was seen in superior and middle frontal gyri, parietal lobule, cingulate cortex and pre- and postcentral gyri when the task was compared to baseline in the subjects with opioid addiction. Further, a negative correlation was seen between the accuracy of task performance and activation ratio for the significant gyri in the subjects with opioid addiction. Interpretation & conclusions: EEG cortical sources revealed the failure of deactivation of default-mode network (DMN) during the task amongst the subjects with opioid addiction. In addition, there was a decrease in the executive function areas in the subjects with opioid addiction. This lack of sufficiently active executive network and persistence of DMN during the task (as compared to baseline) may potentially form the basis of functional impairments in the subjects with opioid addiction.

Cognitive rehabilitation in a case of traumatic brain injury using EEG-based neurofeedback in comparison to conventional methods.

Severe traumatic brain injury residual cognitive impairments significantly impact the quality of life. EEG-based neurofeedback is a technique successfully used in traumatic brain injury and stroke to rehabilitate cognitive and motor sequelae. There are not individualized comparisons of the effects of EEG-based neurofeedback versus conventional neuropsychological rehabilitation. We present a case study of a traumatic brain injury subject in whom eight sessions of a neuropsychological rehabilitation protocol targeting attention, executive functions, and working memory as compared with a personalized EEG-based neurofeedback protocol focused on the electrodes and bands that differed from healthy subjects (F3, F1, Fz, FC3, FC1, and FCz), targeting the inhibition of theta frequency band (3 Hz-7 Hz) in the same number of sessions. Quantitative EEG and neuropsychological testing were performed. Clear benefits of EEG-based neurofeedback were found in divided and sustained attention and several aspects related to visuospatial skills and the processing speed of motor-dependent tasks. Correlative quantitative EEG changes justify the results. EEG-based neurofeedback is probably an excellent complementary technique to be considered to enhance conventional neuropsychological rehabilitation.

Electroencephalographic (EEG) alterations in young women with high subclinical eating pathology levels: a quantitative EEG study.

PURPOSE: To explore electroencephalographic (EEG) alterations in young women with different eating disorder (ED) psychopathology levels. METHODS: Thirty-seven young women completed general and ED psychopathology (i.e., the ED Examination Questionnaire; EDE-Q) measures. EEG power spectra data were investigated in two conditions: (a) 5 min of resting state (RS) and (b) 5 min of RS after a single taste of a milkshake (ML-RS). EEG analyses were performed using exact Low-Resolution Electromagnetic Tomography software (eLORETA). RESULTS: Cluster analysis performed on the EDE-Q responses revealed a group of 17 women with high levels of ED pathology falling into the subclinical (i.e., sub-threshold) EDs category and a group of 20 women with low levels of ED pathology (controls). In the RS conditions, no significant modifications were observed between groups. Compared to controls, women with subclinical EDs showed an increase in theta activity in the parieto-occipital areas in the ML-RS condition. After controlling for body mass index and general psychopathology, theta activity in these brain structures was positively associated with EDE-Q global and subscale (restraint, shape and weight concern) scores. CONCLUSIONS: Our results may reflect the neurophysiological substrate of ED psychopathology core features like shape/weight concerns. Previous brain imaging and qEEG studies with full-syndrome ED patients also underscored the involvement of parieto-occipital areas in ED pathophysiology. These studies also found brain alterations in the RS condition, not observed here. This is notable given that full-syndrome and subclinical EDs are considered as different manifestations of the same disease along a severity spectrum. LEVEL OF EVIDENCE: Level V, cross-sectional, electroencephalographic, descriptive study.

The Analysis of Electroencephalography Changes Before and After a Single Neurofeedback Alpha/Theta Training Session in University Students.

The underlying mechanisms of alpha/theta neurofeedback training have not been fully determined. Therefore, this study aimed to test the changes in the brain state feedback during the alpha/theta training. Twenty-seven healthy participants were trained during a single session of the alpha/theta protocol, and the resting quantitative electroencephalography (QEEG) was assessed before and after training. QEEG was recorded at eight scalp locations (F3, F4, C3, C4, T3, T4, O1, and O2), and the absolute power, relative power, ratio of sensory-motor rhythm beta (SMR) to theta (RST), ratio of SMR-mid beta to theta (RSMT), ratio of mid beta to theta (RMT), ratio of alpha to high beta (RAHB), and scaling exponent of detrended fluctuation analysis by each band were measured. The results indicated a significant increase of absolute alpha power, especially the slow alpha band, at all electrodes except T3 and T4. Moreover, the relative alpha power, especially the slow alpha band, showed a significant increase at all electrodes. The relative theta power showed a significant decrease at all electrodes, except T3. A significant decrease in relative beta power, relative lower beta power and relative mid beta power was observed at O1. RST (at C4, O1, and O2), RSMT and RMT (at F4, C4, O1 and O2), and RAHB (at all electrodes) showed significant increase. Scaling exponents at all electrodes except T3 showed a significant decrease. These findings indicate that a one-time session of alpha/theta training might have the possibility to enhance both vigilance and concentration, thus stabilizing the overall brain function.

Transcranial Doppler combined with quantitative EEG brain function monitoring and outcome prediction in patients with severe acute intracerebral hemorrhage.

BACKGROUND: Neurological deterioration after intracerebral hemorrhage (ICH) is thought to be closely related to increased intracranial pressure (ICP), decreased cerebral blood flow (CBF), and brain metabolism. Transcranial Doppler (TCD) is increasingly used as an indirect measure of ICP, and quantitative EEG (QEEG) can reflect the coupling of CBF and metabolism. We aimed to combine TCD and QEEG to comprehensively assess brain function after ICH and provide prognostic diagnosis. METHODS: We prospectively enrolled patients with severe acute supratentorial (SAS)-ICH from June 2015 to December 2016. Mortality was assessed at 90-day follow-up. We collected demographic data, serological data, and clinical factors, and performed neurophysiological tests at study entry. Quantitative brain function monitoring was performed using a TCD-QEEG recording system at the patient's bedside (NSD-8100; Delica, China). Univariate and multivariable analyses and receiver operating characteristic (ROC) curves were employed to assess the relationships between variables and outcome. RESULTS: Forty-seven patients (67.3 ± 12.6 years; 23 men) were studied. Mortality at 90 days was 55.3%. Statistical results showed there were no significant differences in brain symmetry index between survivors and nonsurvivors, nor between patients and controls (all p > 0.05). Only TCD indicators of the pulsatility index from unaffected hemispheres (UPI) (OR 2.373, CI 1.299-4.335, p = 0.005) and QEEG indicators of the delta/alpha ratio (DAR) (OR 5.306, CI 1.533-18.360, p = 0.008) were independent predictors for clinical outcome. The area under the ROC curve after the combination of UPI and DAR was 0.949, which showed better predictive accuracy compared to individual variables. CONCLUSIONS: In patients with SAS-ICH, multimodal neuromonitoring with TCD combined with QEEG indicated that brain damage caused diffuse changes, and the predictive accuracy after combined use of TCD-QEEG was statistically superior in performance to any single variable, whether clinical or neurophysiological.

Reduction in Alpha Peak Frequency and Coherence on Quantitative Electroencephalography in Patients with Schizophrenia.

BACKGROUND: The aim of the study was to examine the characteristics of alpha wave peak frequency, power, and coherence in patients with schizophrenia. METHODS: Thirty-one patients with schizophrenia and age- and sex-matched subjects with no psychopathology were enrolled. All study participants underwent quantitative electroencephalography (QEEG). Alpha-related values, including peak frequency, power, and coherence, were evaluated. RESULTS: Alpha peak frequency on the Oz area was slower in the schizophrenia group than that in the control group. However, no differences in absolute or relative power were observed between the two groups. Significant reductions in absolute and relative coherence were observed at the C3-C4 and T3-T4 nodes in the patients with schizophrenia. Relative coherence was reduced at the P3-P4 nodes. CONCLUSION: This study focused on alpha variables detected in QEEG as intrinsic values to distinguish schizophrenia from a healthy control. The results suggest decreased alpha peak frequency of the occipital lobe and decreased coherence between the two hemispheres in patients with schizophrenia. A further study could elucidate the causal relationship and biological meaning of the variations in alpha waves in patients with schizophrenia.